(1) Field of the Invention
This invention relates to magnetic resonance imaging apparatus (or MRI apparatus), and more particularly to a technique of remedying a lack of uniformity in the luminance of sectional images obtained with MRI apparatus.
(2) Description of the Related Art
In an MRI apparatus for obtaining sectional images of a particular site such as a shoulder or the spinal column of an examinee, a surface coil is often employed as a coil for receiving nuclear magnetic resonance signals (hereinafter referred to as NMR signals also) released from the examinee. This is because the surface coil provides sectional images of high signal-to-noise ratio. However, the surface coil has such a characteristic that its reception sensitivity lowers with an increase in the distance between the surface coil and an NMR signal source. This results in a lack of uniformity in the sensitivity distribution over an entire sectional image, and hence non-uniformity in the luminance of the sectional image obtained.
Generally, luminance i(x, y) of each pixel in a sectional image obtained (assuming that the sectional image is in x, y plane) may be expressed by a product of luminance j(x, y) of each pixel in an image which should be obtained if the surface coil had a uniform sensitivity distribution, and sensitivity distribution data .alpha.(x, y) (where 0.ltoreq..alpha. (x, y).ltoreq.1) of the surface coil for each pixel in the image, as in the following equation: EQU i(x, y)=j(x, y)*.alpha.(x, y) (1)
Thus, luminance j(x, y) of each pixel in the image which should be obtained if the surface coil had a uniform sensitivity distribution is derived, in conventional practice, from luminance i(x, y) of each pixel in the sectional image actually obtained, using the following equation: ##EQU1##
Conventionally, the sensitivity distribution data of the surface coil is determined by the following methods:
Method 1: PA1 Method 2: PA1 Method 3: PA1 Where sensitivity distribution data is determined by Method 1, a long time is consumed in calculation. In addition, the sensitivity distribution data must be calculated all over again each time a change is made in the shape or position of the surface coil. PA1 a sensitivity distribution identifier for obtaining sensitivity distribution data of the surface coil by extracting low frequency components from spatial frequency of a sectional image obtained; PA1 a correction factor calculator for deriving correction factor data from the sensitivity distribution data, the correction factor data taking a value smaller than an inverse of a minimum value of the sensitivity distribution data when the sensitivity distribution data approaches the minimum value, and a value substantially corresponding to an inverse of a maximum value of the sensitivity distribution data when the sensitivity distribution data approaches the maximum value; and PA1 an output image calculator for calculating a sectional image with improved luminance by applying the correction factor data to the sectional image obtained.
The sensitivity distribution data of the surface coil is calculated by magnetic field analysis. PA2 That is, based on a positional relationship between each pixel in the sectional image obtained and the surface coil, a pixel for which the surface coil is capable of receiving NMR signals with the best sensitivity is identified by magnetic field analysis. The sensitivity of the surface coil for that pixel is set to "1" (maximum sensitivity). Next, reception sensitivity ratios of the other pixels with respect to the sensitivity "1" pixel are computed by magnetic field analysis, based on positional relationships between these pixels and the surface coil. Sensitivity levels of the surface coil for the pixels are determined to obtain sensitivity distribution data .alpha.(x, y). PA2 A uniform phantom is photographed with the MRI apparatus, and sensitivity distribution data .alpha.(x, y) of the surface coil is determined from variations in luminance based on the sensitivity distribution in a sectional image obtained. PA2 Data consisting of low frequency components of spatial frequency of a sectional image obtained with the MRI apparatus is regarded as approximately corresponding to sensitivity distribution data .alpha.(x, y) of the surface coil. Generally, the sensitivity distribution of the surface coil has a gentle gradient, and its spatial frequency is composed mainly of low frequency components. A smoothing filter is applied to the sectional image influenced by such a sensitivity distribution, to extract the low frequency components. These low frequency components are normalized in the range of 0 to 1, to be regarded as approximately corresponding to sensitivity distribution data .alpha.(x, y) of the surface coil.
When sensitivity distribution data .alpha.(x, y) has been determined by either of these methods, luminance i(x, y) of each pixel in the image actually obtained and sensitivity distribution data .alpha.(x, y) of the surface coil for that pixel are substituted into the above equation (2), to derive a sectional image which should be obtained if the surface coil had a uniform sensitivity distribution, i.e. a sectional image with improved uniformity in luminance.
However, the following problems arise from the use of the foregoing methods to determine the sensitivity distribution of the surface coil:
Method 2 involves the trouble of photographing a phantom with the MRI apparatus in order to determine the sensitivity distribution of the surface coil in advance. Moreover, this method requires complex processing to establish an alignment between the sectional image of an examinee photographed with the MRI apparatus and the sensitivity distribution data determined in advance.
Method 3 extracts, each time a sectional image is obtained from an examinee, low frequency components included in the sectional image, and determines approximate sensitivity distribution data of the surface coil Thus, calculation may be carried out in a much shorter time than determining sensitivity distribution data by magnetic field analysis. There is no need to calculate sensitivity distribution data of the surface coil all over again, which is time-consuming, each time a change is made in the shape or position of the surface coil. Further, the sensitivity distribution of the surface coil need not be determined in advance or aligned with sectional images of an examinee. Thus, this method is free from the drawbacks of Methods 1 and 2.
However, Method 3 has the following, different drawback.
In Method 3, low frequency components are extracted from a photographed sectional image to determine sensitivity distribution data. In background portions of the photographed sectional image from which the site under examination is absent, the image value, with noise components excluded, is zero regardless of the sensitivity. The sensitivity distribution data of the background portions determined tends to be small (near zero), representing a sensitivity widely different from actual sensitivity. Consequently, when luminance is corrected with the above equation (2) based on the sectional image photographed and sensitivity distribution data determined, the luminance becomes stressed for the background portions. This results in excessive emphasis placed on noise components appearing in the background portions, thereby lowering image quality.